Product line pricing is an important business problem faced by retailers and other sellers of merchandise who employ dynamic pricing strategies to generate incremental revenue benefits throughout the year. Retailers, among others, have in increasing numbers begun to utilize decision support systems that leverage the large volume of detailed demand data to automate and optimize pricing recommendations. In particular, the statistical modeling of the price elasticity of items based on analyzing the effect of price changes of one product on its demand, or the demand for another product, can be used to optimize the pricing of products.
Known price optimizers, in general, are given a set of items in a product category together with their current prices and demand cross-elasticity. The optimizers then find a new set of prices that would satisfy all business rules and maximize the profit margin by taking into account some soft price constraints and allowed prices.